DEVELOPMENT OF ERP AND OTHER LARGE BUSINESS SYSTEMS IN THE CONTEXT OF NEW TRENDS AND TECHNOLOGIES

This paper presents an overview of terms, concepts, trends and technologies that are relevant to today\u27s business. It describes the basics of data and information integration and flow in a company through a central ERP system with concepts of CRM and SCM. The emergence of big data as a tributary of a huge number of often unstructured data from different sources can become a central problem or opportunity for advancement and achievement of competitive advantages of a company. Ignorance of key figures and/or the non-acceptance of new business conditions, new technologies and possible deployment solutions are the main reasons for non-productivity and poor business performance. To demonstrate the dynamics of appearance and popularity of terms, concepts, trends and technologies this paper offers a tabular overview of the frequencies based on the data from 3 global databases. Meta analysis shows the expected future development of analytical trends and technologies. This paper is intended for those who lead, run and participate in projects of implementation of large software systems, dealing with quality management of business, or want to understand the complexity of this area and the future directions of development

Characterizing and evaluating the quality of software process modeling language: Comparison of ten representative model-based languages

Software organizations are very conscious that deployments of well-defined software processes improve software product development and its quality. Over last decade, many Software Process Modeling Languages (SPMLs) have been proposed to describe and manage software processes. However, each one presents advantages and disadvantages. The main challenge for an organization is to choose the best and most suitable SPML to meet its requirements. This paper proposes a Quality Model (QM) which has been defined conforms to QuEF (Quality Evaluation Framework). This QM allows to compare model-based SPMLs and it could be used by organizations to choose the most useful model-based SPML for their particular requirements. This paper also instances our QM to evaluate and compare 10 representative SPMLs of the various alternative approaches (metamodel-level approaches; SPML based on UML and approaches based on standards). Finally, this paper concludes there are many model-based proposals for SPM, but it is very difficult to establish with could be the commitment to follow. Some non-considered aspects until now have been identified (e.g., validation within enterprise environments, friendly support tools, mechanisms to carry out continuous improvement, mechanisms to establish business rules and elements for software process orchestrating).Ministerio de Economía y Competitividad TIN2016-76956-C3-2-R (POLOLAS

A Framework for Augmenting Building Performance Models Using Machine Learning and Immersive Virtual Environment

Building performance models (BPMs), such as building energy simulation models, have been widely used in building design. Existing BPMs are mainly derived using data from existing buildings. They may not be able to effectively address human-building interactions and lack the capability to address specific contextual factors in buildings under design. The lack of such capability often contributes to the existence of building performance discrepancies, i.e., differences between predicted performance during design and the actual performance. To improve the prediction accuracy of existing BPMs, a computational framework is developed in this dissertation. It combines an existing BPM with context-aware design-specific data involving human-building interactions in new designs by using a machine learning approach. Immersive virtual environments (IVEs) are used to acquire data describing design-specific human-building interactions, a machine learning technique is used to combine data obtained from an existing BPM, and IVEs are used to generate an augmented BPM. The potential of the framework is investigated and evaluated. An artificial neural network (ANN)-based greedy algorithm combines context-aware design-specific data obtained from IVEs with an existing BPM to enhance the simulations of human-building interactions in new designs. The results of the application show the potential of the framework to improve the prediction accuracy of an existing BPM evaluated against data obtained from the physical environment. However, it lacks the ability to determine the appropriate combination between context-aware design-specific data and data of the existing BPM. Consequently, the framework is improved to have ability to determine an appropriate combination based on a specified performance target. A generative adversarial network (GAN) is used to combine context-aware design-specific data and data of an existing BPM using the performance target as guide to generate an augmented BPM. The results confirm the effectiveness of this new framework. The performance of the augmented BPMs generated using the GAN-based framework is significantly better than the updated BPMs generated using the ANN-based greedy algorithm. The framework is completed by incorporating a robustness analysis to assist investigations of robustness of the GAN regarding the uncertainty involved in the input parameters (i.e., an existing BPM and context-aware design-specific data). Overall, this dissertation shows the promising potential of the framework in enhancing performance of BPMs and reducing performance discrepancies between estimations made during design and in performance in actual buildings

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Lean on me: An impact study of mutuality supportive leadership behaviour on employee Lean engagement

Total Quality Management (TQM) has been around in the West since the early 1970s. Over the last 40 years it has advanced from its early form, based around ‘quality circles’, to more advanced forms such as Lean and the now common Business Excellence (BE) models. However, up to 60% of implementations fail to deliver initially anticipated results. Research into Lean/TQM suggests that management commitment and conducive culture are key factors inhibiting subordinate engagement. Yet it is recognised that the ‘softer’ side of TQM is vital for its success and a key dimension of Lean/TQM philosophy. This thesis is a longitudinal study of an organisation in the throes of implementing Lean and struggling to engage its employees. Taking a mutuality perspective, the Behavioural Perspective Model (BPM) provides a framework for understanding the manager-subordinate context and Lean engagement. The BPM, complemented by the incorporation of Deci and Ryan’s Self-Determination Theory (SDT), aids understanding of respondents’ learning history in a complex Lean/TQM environment. An objective of this research was to use the insight gained from taking a behavioural/SDT perspective to improve the ‘softer’, respectful side of TQM deployment as in managerial relational practice, thus enabling improvement in leader-subordinate, day-to-day relations and increased Lean approach behaviour. The thesis is built around three interrelated projects. Project One investigates the deployment context, identifying engagement barriers and opportunities. Project Two, a longitudinal intervention based on mutuality supportive leader-subordinate behaviour, identifies positive affect across three surveys. Project Three, a survey-based study of the whole organisation (n=328), considers both ‘active’ and ‘not-active’ employees, finding significant differences in all key variables between the two groups, identifying ‘work climate’ and motivation as key influences on Lean engagement. This research provides tentative evidence that managerial commitment to a supportive work climate influences subordinate engagement and quality of engagement in Lean/TQM

Donor Family Consent and the Behavioural Perspective Model

Organ transplantation is one of the greatest medical innovations of the 20th century, providing individuals facing death a hope of survival. In the context of the UK this life saving procedure is totally dependent on the altruism of the potential donor’s family. Currently demand for transplantable organs outstrips supply, resulting in 1000 individuals dying each year. Donor family refusal has been consistently identified as the greatest obstacle preventing an improvement in donation rates. The need for new theory and theory driven methods in understanding donation consent has been highlighted in the existent literature. To date there is a notable absence of a theoretical framework that allows for both individual and external level factors to be analysed together, thus providing a truly holistic depiction of this complex human behaviour. This thesis seeks to fill this notable gap by exploring donor family consent from a radical behaviourist perspective via the application of the Behavioural Perspective Model (BPM). Specifically this thesis documents a dual-phase sequential research strategy that seeks to answer three overarching research questions: (1) Can the decision to consent be understood as an operant process? (2) What patterns of reinforcement increase the likelihood of consent? (3) Can donor family consent be stimulated via behavioural intervention? The first empirical phase utilises a case study approach in the exploration of donor family consent, drawing upon multiple sources of evidence (n = 55). The second empirical phase builds upon the findings of the first by utilising a novel simulated laboratory experiment methodology to examine how organ donation consent can be stimulated in different hypothetical scenarios based upon the eight contingency categories of the BPM framework (n= 50). The results of the employed empirical strategy demonstrate the usefulness of the BPM as an interpretative device in this important health context and thus extend its applicability beyond the traditional consumer behaviour domain. Four key findings have resulted from the two empirical phases of this thesis: (1) the role and importance of positive learning history in influencing consent (2) the open behaviour setting preference of donation decision makers (3) the success of informational reinforcement in stimulating consent and (4) the role of pleasure in the consent process. This thesis complements existing organ donation knowledge by adopting a radical behavioural perspective. In addition to making a unique contribution to existing knowledge by offering a new theoretical perspective to this context, the findings of this thesis offer implications for social marketers on the ways in which consent may be stimulated

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse